On the hierarchical Bayesian approach to image restoration: applications to astronomical images

Author

Molina, R.

Author_Institution

Dept. de Ciencias de la Comput. e Inteligencia Artificial, Granada Univ., Spain

Volume

16

Issue

11

fYear

1994

fDate

11/1/1994 12:00:00 AM

Firstpage

1122

Lastpage

1128

Abstract

In an image restoration problem one usually has two different kinds of information. In the first stage, one has knowledge about the structural form of the noise and local characteristics of the restoration. These noise and image models normally depend on unknown hyperparameters. The hierarchical Bayesian approach adds a second stage by putting a hyperprior on the hyperparameters, where information about those hyperparameters is included. In this work the author applies the hierarchical Bayesian approach to image restoration problems and compares it with other approaches in handling the estimation of the hyperparameters

Keywords

Bayes methods; astronomy; image restoration; maximum likelihood estimation; astronomical images; hierarchical Bayesian approach; hyperparameters estimation; hyperprior; image models; image restoration; local characteristics; noise; Astronomy; Bayesian methods; Cameras; Degradation; Focusing; Image restoration; Maximum likelihood estimation; Optical films; Optical noise; Probability distribution;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.334393

Filename

334393